I dedictated my science fair on machine learning. I think it was one of my special interests, since I learned linear algebra and calculus + some statistics to understand how to make one.
I tried making an AI that would learn how to play PuyoPuyo, but I used a single DQL neural network, so it was pretty bad 😅. It just spent its time putting the pieces on the side instead of actually getting more chains.
I even remember telling my classmates about ML during an unrelated presentation, telling them that they should get ready for a new era of advanced AI (I cringe everytime I remember this. Hopefully they forgot lol)
But yeah, chatGPT (or its predecessor. I remeber it being called something else) was pretty fun. I remember annoying my best friends by asking it te generate a donald trump speech on their favorite characters. They were verry annoyed, but nowadays they use AI like it's their second brain haha.
Needless to say, I got to experience beforehand how capitalism ruins certain aspects of innovation. Don't get me wrong, good progress has been made, but I feel like slapping LLMs on every AI problem (or transformers in general) is not the way to go, even if it pleases investors. There are many types of machine learning algorithms out there, for different types of problems. I feel like LLMs are a part of the puzzle, but not enough for AGI, and putting all the ressources into trying to make LLMs what it's not best at doing a waste.
Also for the environmental side… All I'll say is that companies knew the devestating effects on the environment that a large scale ML AI would have. I even remember feeling bad training my AI for the science fair, because I was essentialy leaving my computer open for hours running at max power. If a 14 year old knew this was bad for energy consumption and the environment, you bet google, meta and the rest knew as well.